1. Field of the Invention
This invention relates generally to digital video technology and more particularly to a method and apparatus for detecting unauthorized copies of a digital image based on the content of the image.
2. Description of the Related Art
The success of the Internet and the widespread availability of cost-effective digital storage devices have made it possible to replicate, transmit, and distribute digital content in an effortless way. Thus, the protection of Intellectual Property Rights (IPR), especially with respect to copyrights of digital images, has become crucial legal issue. In particular, detecting copies of digital media (images, audio and video) is a basic requirement for those investigating possible copyright violations. Two applications of copy detection in use include usage tracking and copyright violation enforcement.
Currently, there are two approaches commonly used to protect a copyright of a digital image: watermarking and content-based copy detection. As is generally known, watermarking embeds information into the image prior to distribution. Thus, all copies of the marked content contain the watermark, which can be extracted, to prove ownership. For content-based copy detection additional information, beyond the image itself, is not required. Generally, the image contains enough unique information that can be used for detecting copies, especially illegally distributed copies. For instance, if an owner of an image suspects that the image is being illegally distributed on the Internet, the owner can raise a query to a copy detection system. It should be appreciated that the content-based copy detection can also be a complementary approach to watermarking. After the copy detector provides a creator or a distributor with a suspect list, the actual owner of the media can use a watermark or other authentication techniques to prove ownership.
Content-based copy detection schemes extract signatures from the original images. The same signature, extracted from the test image, is compared to the original image signature to determine if the test image is a copy of the original image. The key advantage of the content-based copy detection over watermarking is the fact that the signature extraction is not required to be conducted before the image is distributed. However, copies that are not the same as the original, i.e., copies that are slightly modified, may not be detected. For example, a third party may generate various modifications to avoid copy detection or enhance image quality which may cause the content based copy detection system not to detect the copy.
Color histogram-based methods, such as the histogram intersection method, have been used in content-based image retrieval systems. However, they are not suitable for copy detection systems since the color histogram does not preserve information about the spatial distribution of colors. Another method which can consider the pixel locations is the partition based approach. In this method, the image is divided into sub-images. In one such method, the color information of each partition is obtained by a local color histogram. The similarity of two images is measured by comparing their local color histogram, and by considering the similarity of all the sub-images. However, this method comes at a high computational cost and requires a long search time. Additionally, this method will not detect images that have their spatial outlay modified.
It is worth noting that there is a fundamental difference between content-based image retrieval and image copy detection. An image copy detector searches for all copies of a query image, whereas a content-based image retrieval system searches for similar images, usually in terms of color. For instance, FIG. 1 shows three images illustrating the differences between image copy detector searches and a content-based image retrieval system. Here, image 102 is an original (or query) image, image 104 is similar to image 102 in terms of color, and image 106 is hue changed from image 102. For the case of a color-based image retrieval system, image 104 is considered more relevant to image 102 than image 106, while image 106 is considered more relevant as a copy of image 102 by an image copy detector. Thus, depending on the type of copy detection method used, different results will be obtained where some image copies are not detected by one or all of the methods used. In other words, an acceptable image copy detector should detect copies tolerating some extent of modifications. The modifications include changes in brightness and saturation, shift in hue, and spatial distortions including rotating, flipping, and so on. One proposal to cover the modifications is to include the use of wavelet-based replicated image detection on the web. However, the wavelet-based method would fail to detect copies with flipping or rotating.
As a result, there is a need to solve the problems of the prior art to provide a method and apparatus for robust and efficient content-based image copy detection of a copy of an original digital image where the copy has been modified either in terms of spatial outlay or color.